NYC Data Science Academy| Blog
Bootcamps
Lifetime Job Support Available Financing Available
Bootcamps
Data Science with Machine Learning Flagship ๐Ÿ† Data Analytics Bootcamp Artificial Intelligence Bootcamp New Release ๐ŸŽ‰
Free Lesson
Intro to Data Science New Release ๐ŸŽ‰
Find Inspiration
Find Alumni with Similar Background
Job Outlook
Occupational Outlook Graduate Outcomes Must See ๐Ÿ”ฅ
Alumni
Success Stories Testimonials Alumni Directory Alumni Exclusive Study Program
Courses
View Bundled Courses
Financing Available
Bootcamp Prep Popular ๐Ÿ”ฅ Data Science Mastery Data Science Launchpad with Python View AI Courses Generative AI for Everyone New ๐ŸŽ‰ Generative AI for Finance New ๐ŸŽ‰ Generative AI for Marketing New ๐ŸŽ‰
Bundle Up
Learn More and Save More
Combination of data science courses.
View Data Science Courses
Beginner
Introductory Python
Intermediate
Data Science Python: Data Analysis and Visualization Popular ๐Ÿ”ฅ Data Science R: Data Analysis and Visualization
Advanced
Data Science Python: Machine Learning Popular ๐Ÿ”ฅ Data Science R: Machine Learning Designing and Implementing Production MLOps New ๐ŸŽ‰ Natural Language Processing for Production (NLP) New ๐ŸŽ‰
Find Inspiration
Get Course Recommendation Must Try ๐Ÿ’Ž An Ultimate Guide to Become a Data Scientist
For Companies
For Companies
Corporate Offerings Hiring Partners Candidate Portfolio Hire Our Graduates
Students Work
Students Work
All Posts Capstone Data Visualization Machine Learning Python Projects R Projects
Tutorials
About
About
About Us Accreditation Contact Us Join Us FAQ Webinars Subscription An Ultimate Guide to
Become a Data Scientist
    Login
NYC Data Science Acedemy
Bootcamps
Courses
Students Work
About
Bootcamps
Bootcamps
Data Science with Machine Learning Flagship
Data Analytics Bootcamp
Artificial Intelligence Bootcamp New Release ๐ŸŽ‰
Free Lessons
Intro to Data Science New Release ๐ŸŽ‰
Find Inspiration
Find Alumni with Similar Background
Job Outlook
Occupational Outlook
Graduate Outcomes Must See ๐Ÿ”ฅ
Alumni
Success Stories
Testimonials
Alumni Directory
Alumni Exclusive Study Program
Courses
Bundles
financing available
View All Bundles
Bootcamp Prep
Data Science Mastery
Data Science Launchpad with Python NEW!
View AI Courses
Generative AI for Everyone
Generative AI for Finance
Generative AI for Marketing
View Data Science Courses
View All Professional Development Courses
Beginner
Introductory Python
Intermediate
Python: Data Analysis and Visualization
R: Data Analysis and Visualization
Advanced
Python: Machine Learning
R: Machine Learning
Designing and Implementing Production MLOps
Natural Language Processing for Production (NLP)
For Companies
Corporate Offerings
Hiring Partners
Candidate Portfolio
Hire Our Graduates
Students Work
All Posts
Capstone
Data Visualization
Machine Learning
Python Projects
R Projects
About
Accreditation
About Us
Contact Us
Join Us
FAQ
Webinars
Subscription
An Ultimate Guide to Become a Data Scientist
Tutorials
Data Analytics
  • Learn Pandas
  • Learn NumPy
  • Learn SciPy
  • Learn Matplotlib
Machine Learning
  • Boosting
  • Random Forest
  • Linear Regression
  • Decision Tree
  • PCA
Interview by Companies
  • JPMC
  • Google
  • Facebook
Artificial Intelligence
  • Learn Generative AI
  • Learn ChatGPT-3.5
  • Learn ChatGPT-4
  • Learn Google Bard
Coding
  • Learn Python
  • Learn SQL
  • Learn MySQL
  • Learn NoSQL
  • Learn PySpark
  • Learn PyTorch
Interview Questions
  • Python Hard
  • R Easy
  • R Hard
  • SQL Easy
  • SQL Hard
  • Python Easy
Data Science Blog > Data Visualization > Goodreads: An Analysis of Data Trends in Reader Behavior

Goodreads: An Analysis of Data Trends in Reader Behavior

Trevor Ban
Posted on Aug 2, 2021
The skills I demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.

Goodreads: An Analysis of Data Trends in Reader Behavior

Github Repository

For any book publisher wanting to optimize decision-making regarding who, what, and when to publish, Goodreads presents an unprecedented look into the behaviors and wishes of the book-reading world. Goodreads is the world's largest book recommendation site with over 90 million users. Thought it is difficult to know our audience, the data provided by Goodreads can help us become far more acquainted with the readers of the world.  As a long-time user of Goodreads, I was thrilled to begin such a project.

 

Using a dataset scraped by Austin Reese, which was itself based on a list of 50,000 books on Goodreads, I set out to better understand today's publishing and reading trends. Although this analysis is in no way comprehensive, it does provide an insightful visual exploration into today's readers. Using rating counts as a proxy for popularity and sales, we will be exploring which features maximize both rating count and average rating.

This exploration will be framed around the following 6 questions:

  1. Does page number have an impact on popularity and rating?
  2. What impact does being a part of a series have?
  3. Do awards have an impact?
  4. What are the most popular genres?
  5. What keywords are most popular in book descriptions?
  6. Are there any trends present regarding the sex of the author?

Initial Data On Rating and Books

First, let's take a general glance at the data.

It appears to be normally distributed, but with suspicious spikes around the 3.5, 4, 4.5, and 5 marks. These spikes appear to be from books that weren't popular enough to get enough ratings to throw them into the 'gray area' between user-provided ratings. Let's see what happens if we remove all books with fewer than 1,000 ratings.

Goodreads: An Analysis of Data Trends in Reader Behavior

That's more like it. In addition to appearing much more evenly distributed, there was a substantial drop in the standard deviation (0.345 -> 0.266).  Now, let's take an overview of correlations via the heatmap.

Goodreads: An Analysis of Data Trends in Reader Behavior

The heatmap suggests that there may be a connection between the average rating and the number of pages the book has. It does not suggest, however, that longer book will be more popular. Let's dig a little deeper to confirm this.

Data on Page Number and Book Rating and Popularity

The vast majority of books seem to be centered around the 300-500 page zone. This visualization also suggests that as books get longer, the ratings generally improve. But what about popularity?

As expected, the longer books, though higher rated, are rarely popular. The majority of popular books seem to be in the 200-800 page range.

Data on Book Series Popularity

My initial guess was that books in a series would be more popular and lower rated than their non-series counterparts. This guess turned out to be very, very wrong.

Books that are part of a series appear to be roughly equally popular and higher rated than there non-series counterparts. This was a surprising finding.

What impact do awards have?

The following is a comparision of books that have received an award (any award) and books that have not.

It seems to be that awarded books tend to be far more popular while, surprisingly, being equally rated to their non-awarded counterparts.

What genres seem to be trending?

Provided below is an admittedly crude assessment of changes in the number of book publications by genre over the past 70 years.

Though a much more granular assessment of genre trends is needed, this graph still reveals a few interesting trends; Fantasy shows an incredibly steady growth in popularity while Young Adult and Romance books have enjoyed a large growth in popularity over the past 20 years. It is also worth noting that the majority of the 'mega popular' books are in the Young Adult (Harry Potter, Hunger Games, Twilight, Divergent, etc.) and Romance (Fifty Shades of Gray) genres.

What keywords are most common in book descriptions?

This wordcloud provides an entertaining look into book descriptions over the past 50 years.

It's hard to glean anything definitive from it, but at a quick glance, it seems to be that relational words (family, mother, father, friends) and 'absolute' words (never, first, everything) are very common among book descriptions.

What trends can be found in publications by the sex of the author?

If we first look at the percent difference in publications by male vs female authors over the past 70 years, a striking trend is revealed.

From the 1950s through 2000, the majority of books published by year were primarily from male authors. Starting around 1990, this begins to shift until, in 2005, male and female authors are equally represented among publications. Now, it seems, most of the book publications are consistently from female authors for the first time in history - or, at least, in this dataset ๐Ÿ™‚

If we again look at the percent difference in publications of male and female authors, except only including the books that have received an award, another interesting trend reveals itself.

With the exception of a notable spike in 2002, the same trend is revealed, though set back about 4 years. The turning point of equal publications of awarded books is at 2009, rather than the above 2005 turning point for equal book publications. It seems to be that the trend in awarded books by author sex is trailing about 4 years behind the same trend found in book publications by author sex.

What were our limitations?

Before I summarize the major findings of this analysis, I want to quickly note the following limitations of this study:

  • The dataset was large, but in no way comprehensive.
  • Using the number of book ratings as a proxy for sales, though useful, is hardly a sufficient replacement.
  • The genre analysis was very crude and based on a limited set of genres.
  • in addition, the genre trends were based on the number of books published in that genre by year, and was not weighted by book popularity.
  • The authors' sex was predicted based on the authors' first name.
  • This study focused on trends in the authors' sex, and did not take into account a diverse range of genders.

    Now, at last, the main findings...

  • Longer books, though higher rated, are predictably less popular.
  • Awarded books are more much popular, but similarly rated to non-awarded books
  • Series seem to be higher rated, but not much more popular than non-series books
  • Young Adult, Romance and Fantasy books seem to be trending
  • Book publications seem to be trending towards female authors
  • Awarded book publications by author sex seem to reflect the trend in book publications, though it seems to be trailing just a few years behind

    Conclusion:

In the future, this assessment will provide, in addition to fixes to the aforementioned limitations, an analysis of the relationship between book price and book length, something this dataset did not allow.

With book publishing being such a vast, though recently challenged, industry, it is more important than ever to know what readers want. Using this and future analyses of information provided by Goodreads' vast userbase, book publishers can make wiser decisions regarding who, what, and when to publish. Now... Go read a book.

About Author

Trevor Ban

Trevor Ban is a Data Analyst at Mercy College focusing on improving student outcomes. He is currently pursuing his Masters's Degree in Computer Science with a focus on Data Science. He has a background in Chemistry and Psychology...
View all posts by Trevor Ban >

Leave a Comment

No comments found.

View Posts by Categories

All Posts 2399 posts
AI 7 posts
AI Agent 2 posts
AI-based hotel recommendation 1 posts
AIForGood 1 posts
Alumni 60 posts
Animated Maps 1 posts
APIs 41 posts
Artificial Intelligence 2 posts
Artificial Intelligence 2 posts
AWS 13 posts
Banking 1 posts
Big Data 50 posts
Branch Analysis 1 posts
Capstone 206 posts
Career Education 7 posts
CLIP 1 posts
Community 72 posts
Congestion Zone 1 posts
Content Recommendation 1 posts
Cosine SImilarity 1 posts
Data Analysis 5 posts
Data Engineering 1 posts
Data Engineering 3 posts
Data Science 7 posts
Data Science News and Sharing 73 posts
Data Visualization 324 posts
Events 5 posts
Featured 37 posts
Function calling 1 posts
FutureTech 1 posts
Generative AI 5 posts
Hadoop 13 posts
Image Classification 1 posts
Innovation 2 posts
Kmeans Cluster 1 posts
LLM 6 posts
Machine Learning 364 posts
Marketing 1 posts
Meetup 144 posts
MLOPs 1 posts
Model Deployment 1 posts
Nagamas69 1 posts
NLP 1 posts
OpenAI 5 posts
OpenNYC Data 1 posts
pySpark 1 posts
Python 16 posts
Python 458 posts
Python data analysis 4 posts
Python Shiny 2 posts
R 404 posts
R Data Analysis 1 posts
R Shiny 560 posts
R Visualization 445 posts
RAG 1 posts
RoBERTa 1 posts
semantic rearch 2 posts
Spark 17 posts
SQL 1 posts
Streamlit 2 posts
Student Works 1687 posts
Tableau 12 posts
TensorFlow 3 posts
Traffic 1 posts
User Preference Modeling 1 posts
Vector database 2 posts
Web Scraping 483 posts
wukong138 1 posts

Our Recent Popular Posts

AI 4 AI: ChatGPT Unifies My Blog Posts
by Vinod Chugani
Dec 18, 2022
Meet Your Machine Learning Mentors: Kyle Gallatin
by Vivian Zhang
Nov 4, 2020
NICU Admissions and CCHD: Predicting Based on Data Analysis
by Paul Lee, Aron Berke, Bee Kim, Bettina Meier and Ira Villar
Jan 7, 2020

View Posts by Tags

#python #trainwithnycdsa 2019 2020 Revenue 3-points agriculture air quality airbnb airline alcohol Alex Baransky algorithm alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus ames dataset ames housing dataset apartment rent API Application artist aws bank loans beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep boston safety Bundles cake recipe California Cancer Research capstone car price Career Career Day ChatGPT citibike classic cars classpass clustering Coding Course Demo Course Report covid 19 credit credit card crime frequency crops D3.js data data analysis Data Analyst data analytics data for tripadvisor reviews data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization database Deep Learning Demo Day Discount disney dplyr drug data e-commerce economy employee employee burnout employer networking environment feature engineering Finance Financial Data Science fitness studio Flask flight delay football gbm Get Hired ggplot2 googleVis H20 Hadoop hallmark holiday movie happiness healthcare frauds higgs boson Hiring hiring partner events Hiring Partners hotels housing housing data housing predictions housing price hy-vee Income industry Industry Experts Injuries Instructor Blog Instructor Interview insurance italki Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter las vegas airport lasso regression Lead Data Scienctist Lead Data Scientist leaflet league linear regression Logistic Regression machine learning Maps market matplotlib Medical Research Meet the team meetup methal health miami beach movie music Napoli NBA netflix Networking neural network Neural networks New Courses NHL nlp NYC NYC Data Science nyc data science academy NYC Open Data nyc property NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time performance phoenix pollutants Portfolio Development precision measurement prediction Prework Programming public safety PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R Data Analysis R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn seafood type Selenium sentiment analysis sentiment classification Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau teachers team team performance TensorFlow Testimonial tf-idf Top Data Science Bootcamp Top manufacturing companies Transfers tweets twitter videos visualization wallstreet wallstreetbets web scraping Weekend Course What to expect whiskey whiskeyadvocate wildfire word cloud word2vec XGBoost yelp youtube trending ZORI

NYC Data Science Academy

NYC Data Science Academy teaches data science, trains companies and their employees to better profit from data, excels at big data project consulting, and connects trained Data Scientists to our industry.

NYC Data Science Academy is licensed by New York State Education Department.

Get detailed curriculum information about our
amazing bootcamp!

Please enter a valid email address
Sign up completed. Thank you!

Offerings

  • HOME
  • DATA SCIENCE BOOTCAMP
  • ONLINE DATA SCIENCE BOOTCAMP
  • Professional Development Courses
  • CORPORATE OFFERINGS
  • HIRING PARTNERS
  • About

  • About Us
  • Alumni
  • Blog
  • FAQ
  • Contact Us
  • Refund Policy
  • Join Us
  • SOCIAL MEDIA

    ยฉ 2025 NYC Data Science Academy
    All rights reserved. | Site Map
    Privacy Policy | Terms of Service
    Bootcamp Application